Papers by Tim Polzehl

2 papers
Towards a Reliable and Robust Methodology for Crowd-Based Subjective Quality Assessment of Query-Based Extractive Text Summarization (2020.lrec-1)

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Challenge: a growing number of documents are needed for multi-document summarization.
Approach: They propose crowdsourcing to evaluate intrinsic and extrinsic quality of extractive text summaries . they conduct intensive comparative crowdsourcing and laboratory experiments .
Outcome: The proposed crowdsourcing task evaluates intrinsic and extrinsic quality of extractive text summaries.
Comprehensive Layer-wise Analysis of SSL Models for Audio Deepfake Detection (2025.findings-naacl)

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Challenge: Existing algorithms for audio deepfake detection are based on layer-wise analysis of self-supervised learning (SSL) models.
Approach: They conduct a layer-wise analysis of self-supervised learning (SSL) models for audio deepfake detection across diverse contexts.
Outcome: The proposed models achieve competitive equal error rate (EER) scores even when employing a reduced number of layers.

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